Adding transparency to traded markets with physical sensor data.
The search for signals and trends to aid trading decisions in commodities, energy and agricultural markets is often focused on data that the market itself produces. This data (prices, traded volumes etc.) is readily accessible and constantly generated by the market. When coupled with limited commodity owner-operator reported data and known external supply and demand drivers, such as weather, supply, pricing and demand behavior are modeled to inform future trading strategies. Existing in parallel to this traditional data space and its data mining and modeling activities, is the physical world where the actual commodity is generated, transferred from one location on the earth to another and ultimately processed and consumed. Real-time operational dynamics such as equipment failure and transport disruptions often disrupt what the market data derived models predict.
In the physical world, sensor data and sensing systems are commonplace. The owner-operators of traded physical commodities depend on a range of sensors, systems and signals to drive real-time decision making and operational awareness and the ability to draw conclusions from the past and predict future behavior. When sensors and sensing techniques generally found in operational engineering fields are targeted at delivering real-time intelligence in traded markets, a new source of market data emerges which not only adds greater, real-time transparency, but allows traditional price, supply and demand models to tap directly into the physical marketplace for input.
How does one go about determining what sensors to use and what to measure in the real world to capture intelligence on the physical market-place? The answer frequently lies in the infrastructure responsible for generating, transferring, processing and consuming a particular commodity. This infrastructure is composed of many forms of machines or systems and each system readily gives off signatures and signals detailing its operational state and level of activity.
For example, the infrastructure driving the global oil supply chain is comprised of production units (i.e., wells, drills, etc.), storage units (i.e., tanks, underground caverns, etc.), refining and processing units (i.e., distillation, fractionation, etc.) and a host of transportation elements (i.e., pipelines, trucks, rail cars, ships, etc.). All such infrastructure involve detectable signals in the form of sound, light, heat, volume, flow rates, airborne emissions, electromagnetic fields (EMF), radio-frequency transmissions, etc. Conveniently an abundance of sensors exist to interrogate such signals and certain sensors can be used in many different sensing applications. The signals associated with any specific infrastructure element can be sensed remotely, from single to many miles away, without needing to be in close proximity.
A thermal imaging camera (more commonly used in night vision and security applications) can detect whether a petrochemical refining unit is operating or not by imaging the radiated heat and airborne emissions from the unit. The same sensor can determine what the volume of oil being stored in a tank is due to the intrinsic contrast between the temperature of the oil in the tank, the tank itself and gas-filled spaces in the tank (Figure 1). When the thermal camera is focused on a power plant, an oil pumping station, a natural gas storage facility or a biofuels processing facility, the operational state of units is visible via heat and emissions from various machinery inside these facilities.
Magnetic-field sensing devices (more commonly employed in street traffic monitoring) readily pick up the magnetic field surrounding the current carrying conductors that comprise high voltage transmission power lines. These magnetic fields hold the key to understanding the amount of electrical power flowing in the power line at any point in time. When magnetic field measuring devices are deployed at scale to many power lines surrounding power generation plants or stations, the combined sensor data gives insight into regional and national electric grid power generation and flows.
Ships traveling from port to port with cargo that drives global trade are as easily detected as the electrons flowing in a power line or the heat radiated from units at an oil refinery. Among other signatures emanating from a seaborne vessel are collision avoidance or Automatic Identification System (AIS) messages. These radio frequency broadcasts are not only detectable using standard radio receivers on the earth but from hundreds of miles out in space from receivers aboard low-earth orbiting satellites.
From assessing the height of an ear of corn in a field, to capturing the volume of crude oil stored in a tank using aerial or satellite imaging, to measuring the current flow in a high voltage power line or the operation of a compressor at a natural gas storage hub, or observing the pumping action on a mainline crude oil pipeline, a host of remote-sensing technologies are increasingly available to allow real-time physical market transparency. At one time, physical global markets may have been thought to be too large, too geographically dispersed, or too complex to monitor on a real-time basis. This is no longer the case, as sensors traditionally used in non market-related fields such as engineering, science and medicine are employed to capture signals which track real-time commodity generation, transfer, processing and consumption and can then relay the resulting information into the marketplace to expand transparency and inform decision making.
About the author
Deirdre Alphenaar is chief R&D officer at Genscape. Previously, she worked as the director of Information Technology for Telemics, Inc. Before moving to the United States in 2000, she held a research associate position at the University of Cambridge, England, following a Ph.D. in Physics (University of Surrey), and a master’s in Medical Radiation Physics (Charing Cross Medical School/Brunel University). Deirdre has authored over 15 scientific publications and manages the Genscape patent portfolio, and currently holds seven US and several international patents.
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For more insight into how Genscape utilizes a range of proprietary sensors and monitoring technologies to provide market transparency: www.genscape.com